Increments and duplication events of enzymes and transcription factors influence metabolic and regulatory diversity in prokaryotes

Abstract

In this work, the content of enzymes and DNA-binding transcription factors (TFs) in 794 non-redundant prokaryotic genomes was evaluated. The identification of enzymes was based on annotations deposited in the KEGG database as well as in databases of functional domains (COG and PFAM) and structural domains (Superfamily). For identifications of the TFs, hidden Markov profiles were constructed based on well-known transcriptional regulatory families. From these analyses, we obtained diverse and interesting results, such as the negative rate of incremental changes in the number of detected enzymes with respect to the genome size. On the contrary, for TFs the rate incremented as the complexity of genome increased. This inverse related performance shapes the diversity of metabolic and regulatory networks and impacts the availability of enzymes and TFs. Furthermore, the intersection of the derivatives between enzymes and TFs was identified at 9,659 genes, after this point, the regulatory complexity grows faster than metabolic complexity. In addition, TFs have a low number of duplications, in contrast to the apparent high number of duplications associated with enzymes. Despite the greater number of duplicated enzymes versus TFs, the increment by which duplicates appear is higher in TFs. A lower proportion of enzymes among archaeal genomes (22%) than in the bacterial ones (27%) was also found. This low proportion might be compensated by the interconnection between the metabolic pathways in Archaea. A similar proportion was also found for the archaeal TFs, for which the formation of regulatory complexes has been proposed. Finally, an enrichment of multifunctional enzymes in Bacteria, as a mechanism of ecological adaptation, was detected.

Figure 1. Abundance of enzymes as a function of genome size.

On the x axis, genomes are sorted by the number of ORFs. The abundance of enzymes for each genome is shown on the y axis. Each dot corresponds to one genome. Bacteria and Archaea genomes are indicated by gray and filled or red and empty dots, respectively. The power-law function (black line) and R² adjustment are also indicated y = 1.1378x ^0.7883.

Figure 2. Abundance of different E.C. classes in Bacteria and Archaea genomes.

On the x axis, genomes are sorted by the number of ORFs. The abundance of the six E.C. classes is shown in y axis.

Figure 3. Abundance of TFs as a function of genome size.

On the x axis, genomes are sorted by the number of ORFs. The abundance of TFs for each genome is shown on the y axis. The power-law equation (black line) and R² adjustment are also indicated. y = 4.44e-05x ^1.8044. Gray filled points represent Bacteria; red empty points represent Archaea.

Figure 4. Derivatives of enzymes and TFs abundances.

The increments of enzymes and TFs ORFs (y axis) were estimated from the derivatives of metabolic (solid green line) and regulatory (blue dashed line) functions, calculated as a function of the genome size (x axis).

Figure 5. Abundance of duplicated enzymes and TFs as a function of genome size.

The total numbers of all duplicated enzymes and TFs were calculated for each species (y axis) and plotted against the sizes of the 794 species, in ORFs (x axis). The power-law equation and R² adjustment are also indicated. The power-law fitting function is shown by the black dashed line (enzymes) and the red solid line (TFs). Gray filled points represent enzymes; red empty points represent TFs.